Epigenetic Regulation of Skin Development and Regeneration / / edited by Vladimir A. Botchkarev, Sarah E. Millar

• Record Nr.: UNINA9910298406503321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Humana, , 2018
• ISBN: 3-319-16769-3
• Edizione: [1st ed. 2018.]
• Descrizione fisica: 1 online resource (330 pages)
• Collana: Stem Cell Biology and Regenerative Medicine, , 2196-8985
• Disciplina: 572.645
• Soggetti: Stem cells; Regenerative medicine; Tissue engineering; Dermatology; Stem Cells; Regenerative Medicine/Tissue Engineering
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Preface -- Chapter 1 All Roads Go to the Nucleus -- Chapter 2 DNA methylation as an epigenetic memory keeper during skin development and regeneration -- Chapter 3 Polycomb genes and their roles in skin development and regeneration -- Chapter 4 Trithorax genes in the control of keratinocyte differentiation -- Chapter 5 Histone deacetylase functions in epidermal development, homeostasis and cancer -- Chapter 6 The role of ATP-dependent chromatin remodeling in the control of epidermal differentiation and skin stem cell activity -- Chapter 7 Orchestrated Role of microRNAs in Skin Development and Regeneration -- Chapter 8 Non-coding genome and its role in the control of gene expression -- Chapter 9 RNA modifications in the control of epidermal differentiation and stem cell activity -- Chapter 10 Enhancer-Promoter Interactions and Their Role in the Control of Epidermal Differentiation -- Chapter 11 Nuclear lamina as an interface between cytoskeleton and chromatin -- Chapter 12 Epigenetic mechanisms in the control of skin wound healing.
• Sommario/riassunto: This indispensable volume highlights recent studies identifying ; epigenetic mechanisms as essential regulators of skin development, stem cell activity and regeneration. Chapters are contributed by leading experts and promote the skin as an accessible model system for studying mechanisms that control organ development and regeneration. The timely discussions contained throughout are of broad relevance to other areas of biology and medicine and can help inform the development of novel therapeutics for skin disorders as well as new approaches to skin regeneration that target the epigenome. Part of the highly successful Stem Cells and Regenerative Medicine series, Epigenetic Regulation of Skin Development and Regeneration uncovers the fundamental significance of epigenetic mechanisms in skin development and regeneration, and emphasizes the development of new therapies for a number of skin disorders, such as pathological conditions of epidermal differentiation, pigmentation and carcinogenesis. At least six categories of researchers will find this book essential, including stem cell, developmental, hair follicle or molecular biologists, and gerontologists or clinical dermatologists. .

Forest Pathology and Entomology

• Record Nr.: UNINA9910557486803321
• Autore: Moricca Salvatore
• Pubbl/distr/stampa: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (301 p.)
• Soggetti: Biology, life sciences; Forestry & related industries; Research & information: general
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Sommario/riassunto: The 22 papers that make up this Special Issue deal with pathogen and ; pest impact on forest health, from the diagnosis to the surveillance of causative agents, from the study of parasites' biological, epidemiological, and ecological traits to their correct taxonomy and classification, and from disease and pest monitoring to sustainable control strategies.

Neural Information Processing : 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12–15, 2019, Proceedings, Part III / / edited by Tom Gedeon, Kok Wai Wong, Minho Lee

• Record Nr.: UNINA9910364955003321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
• ISBN: 3-030-36718-5
• Edizione: [1st ed. 2019.]
• Descrizione fisica: 1 online resource (662 pages)
• Collana: Theoretical Computer Science and General Issues, , 2512-2029 ; ; 11955
• Disciplina: 006.32; 006.4 (edition:23)
• Soggetti: Pattern recognition systems; Artificial intelligence; Computer vision; Application software; Computers, Special purpose; Automated Pattern Recognition; Artificial Intelligence; Computer Vision; Computer and Information Systems Applications; Special Purpose and Application-Based Systems
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Semantic and Graph Based Approaches -- GL2vec: Graph Embedding Enriched by Line graphs with Edge Features -- Joint Semantic Hashing using Deep Supervised and Unsupervised Methods -- Label-Based ; Deep Semantic Hashing for Cross-Modal Retrieval -- HRec: Heterogeneous Graph Embedding-Based Personalized Point-of-Interest Recommendation -- Embedding and Predicting Software Security Entity Relationships: A Knowledge Graph Based Approach -- SACIC: A Semantics-aware Convolutional Image Captioner using Multi-Level Pervasive Attention -- One Analog Neuron Cannot Recognize Deterministic Context-Free Languages -- Tag-based Semantic Features for Scene Image Classification -- Integrating TM Knowledge into NMT with Double Chain Graph -- Learning Transferable Policies with Improved Graph Neural Networks on Serial Robotic Structure -- Visualizing Readable Instance Graphs of Ontology with Memo Graph -- Spiking Neuron and Related Models -- Hippocampus Segmentation in MRI Using Side U-Net Model -- AutoMLfor DenseNet Compression -- Mechanisms of Reward-Modulated STDP and Winner-Take-All in Bayesian Spiking Decision-Making Circuit -- Homeostasis-based CNN-to-SNN Conversion of Inception and Residual Architectures -- Training Large-Scale Spiking Neural Networks on Multi-core Neuromorphic System Using Backpropagation -- Deep learning of EEG Data in the NeuCube Brain-inspired Spiking Neutral Network Architecture for a Better Understanding of Depression -- Text Computing Using Neural Techniques -- Watch and Ask: Video Question Generation -- Multi-Perspective Denoising Reader for Multi-Paragraph Reading Comprehension -- Models in the Wild: On Corruption Robustness of Neural NLP Systems -- Hie-Transformer: A Hierarchical Hybrid Transformer for Abstractive Article Summarization -- Target-Based Attention Model for Aspect-Level Sentiment Analysis -- Keyphrase Generation with Word Attention -- Dynamic Neural Language Models -- A Fast Convolutional Self-attention Based Speech Dereverberation Method forRobust Speech Recognition -- Option Attentive Capsule Network for Multi-choice Reading Comprehension -- Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning -- Paragraph-Level Hierarchical Neural Machine Translation -- Residual Connection-based Multi-step Reasoning via Commonsense Knowledge for Multiple Choice Machine Reading Comprehension -- Zero-Shot Transfer Learning Based on Visual and Textual Resemblance -- Morphological Knowledge Guided Mongolian Constituent Parsing -- BERT based Hierarchical Sequence Classification for Context-aware Microblog Sentiment Analysis -- Topic Aware Context Modelling for Conversation Response Generation -- What a Dialogue! A Deep Neural Framework for Contextual Affect Detection -- Improving student forum responsiveness: Detecting Duplicate Questions in Educational Forums -- Time-series and Related Models -- On Probability Calibration of Recurrent Text Recognition Network -- On the Hermite Series-Based Generalized Regression Neural Networks for Stream Data Mining -- Deep Hybrid Spatiotemporal networks for Continuous Pain Intensity Estimation -- Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology -- Deep Point-wise Prediction for Action Temporal Proposal -- Real-time Financial Data Prediction Using Meta-cognitive Recurrent Kernel Online Sequential Extreme Learning Machine -- Deep Spatial-Temporal Field for Human Head Orientation Estimation -- Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People -- Teacher-Student Learning and Post-Processing for Robust BiLSTM Mask-Based Acoustic Beamforming -- Maxout into MDLSTM for offline Arabic handwriting recognition -- Unsupervised Neural Models -- Unsupervised Feature Selection Based on Matrix Factorization with Redundancy Minimization -- Distance estimation for Quantum Prototypes based Clustering -- Accelerating Bag-of-Words with SOM -- ; A Deep Clustering-Guide Learning for Unsupervised Person Re-identification -- Semi-Supervised Deep Learning Using Unsupervised Discriminant Projection -- Unsupervised pre-training of the brain connectivity dynamic using residual D-net -- Clustering Ensemble Selection with Determinantal Point Processes -- Generative Histogram-based Model using Unsupervised Learning.
• Sommario/riassunto: The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 11955, is organized in topical sections on semantic and graph based approaches; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.